HYPERCAPNBIC NORMALIZATION OF BOLD FMRI: COMPARISON ACROSS FIELD STRENGTHS & PU

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This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. The blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signal response to neural stimulation is influenced by many factors that are unrelated to the stimulus. These factors are physiological, such as the resting venous cerebral blood volume (CBV(v)) and vessel size, as well as experimental, such as pulse sequence and static magnetic field strength (B(0)). Thus, it is difficult to compare task-induced fMRI signals across subjects, field strengths, and pulse sequences. This problem can be overcome by normalizing the neural activity-induced BOLD fMRI response by a global hypercapnia-induced BOLD signal. To demonstrate the effectiveness of the BOLD normalization approach, gradient-echo BOLD fMRI at 1.5, 4, and 7 T and spin-echo BOLD fMRI at 4 T were performed in human subjects. For neural stimulation, subjects performed sequential finger movements at 2 Hz, while for global stimulation, subjects breathed a 5% CO(2) gas mixture. Under all conditions, voxels containing primarily large veins and those containing primarily active tissue (i.e., capillaries and small veins) showed distinguishable behavior after hypercapnic normalization. This allowed functional activity to be more accurately localized and quantified based on changes in venous blood oxygenation alone. The normalized BOLD signal induced by the motor task was consistent across different magnetic fields and pulse sequences, and corresponded well with cerebral blood flow measurements. Our data suggest that the hypercapnic normalization approach can improve the spatial specificity and interpretation of BOLD signals, allowing comparison of BOLD signals across subjects, field strengths, and pulse sequences. A theoretical framework for this method is provided.